Stopwords are words that carry little semantic information and, as a result, are often omitted when performing natural language processing (NLP) tasks. Originally used to accelerate document retrieval and search engine algorithms, stopwords are now commonly applied to NLP tasks involving machine learning, such as model training [1]}. Removing stopwords can reduce dataset size, which can lead to faster training on less sophisticated hardware; removing stopwords can also improve model performance [2]}, [3]}.
